{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d4a2db94-d079-4ce0-8a3e-9090d68f8f9e",
   "metadata": {},
   "source": [
    "For the full example to run the backtesting, refer to [gridtrading.ipynb](https://github.com/nkaz001/hftbacktest/blob/master/hftbacktest/examples/gridtrading.ipynb). This file shows how to trade multiple pairs. For more details of trading multiple assets, please see [Making Multiple Markets - Introduction](https://hftbacktest.readthedocs.io/en/latest/tutorials/Making%20Multiple%20Markets%20-%20Introduction.html).\n",
    "\n",
    "Ran on June 18, 2024, using May 2024 data. Assets onboarded before May 1, 2024, are selected, excluding BTC and ETH.\n",
    "\n",
    "Since the latest tick size is used for backtesting, if the tick size has changed during the backtesting period, the results may be incorrect. Accurate backtesting requires historical tick size data or estimating the tick size daily based on the available data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6002f747-96fb-4baf-891d-1926d3af16b5",
   "metadata": {},
   "source": [
    "## With the highest maker rebates of 0.005%."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a5f864ab-36b2-4eda-b102-504220660897",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import re\n",
    "import json\n",
    "import os.path\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "out_path = './out'\n",
    "sel_pairs = []\n",
    "sel_pairs_total_equity = None\n",
    "\n",
    "with open('tickers_256.json', 'r') as f:\n",
    "    tickers = json.load(f)\n",
    "\n",
    "for i, symbol in enumerate(tickers.keys()):\n",
    "    df = pd.read_csv(os.path.join(out_path, f'{symbol}0.csv'))\n",
    "    df.index = pd.to_datetime(df['timestamp'])\n",
    "    equity = df['balance'] + df['position'] * df['mid_price'] - df['fee']\n",
    "\n",
    "    equity_5min = equity.resample('5min').last()\n",
    "\n",
    "    notional_trade_value = df['position'].diff().abs().rolling('1d').sum().resample('1d').last() * df['mid_price'].resample('1d').last()\n",
    "    # order_qty is set to approximately $100.\n",
    "    approx_num_trades = notional_trade_value / 100\n",
    "    avg_approx_num_trades = approx_num_trades.mean()\n",
    "\n",
    "    # Due to size limitations, individual equity curves are cleared in the output.\n",
    "    fig = plt.figure(i, figsize=(12, 6))\n",
    "    ax = fig.add_subplot(111)\n",
    "    ax.set_title(f'{symbol}, approximate number of average daily trades: {avg_approx_num_trades:.0f}')\n",
    "    ax.set_ylabel('Equity $')\n",
    "    ax.plot(equity_5min)\n",
    "    ax.legend(['Equity'])\n",
    "    ax_pos = ax.twinx()\n",
    "    ax_pos.set_ylabel('Position Qty')\n",
    "    ax_pos.plot(df['position'].resample('5min').last(), 'gray', alpha=0.5)\n",
    "    ax_pos.legend(['Position Qty'])\n",
    "\n",
    "    # Selects only the positive ones, we will test this set in different months and the forward month as well.\n",
    "    if equity.iloc[-1] > 0:\n",
    "        sel_pairs.append(symbol)\n",
    "        if sel_pairs_total_equity is None:\n",
    "            sel_pairs_total_equity = equity_5min\n",
    "        else:\n",
    "            sel_pairs_total_equity += equity_5min"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a340bf56-4316-4f6b-a7bb-09e39ca3042f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fc3f2f16d50>]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "plt.title(f'{len(sel_pairs)} pairs are selected out of {len(tickers)}')\n",
    "plt.ylabel('Equity $')\n",
    "plt.plot(sel_pairs_total_equity)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f41c512-70f3-44b5-9358-ffa72bec020e",
   "metadata": {},
   "source": [
    "## With the zero maker fee 0.0%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "559597fd-5072-4a8a-b5af-794f549eeb54",
   "metadata": {},
   "outputs": [],
   "source": [
    "sel_pairs = []\n",
    "sel_pairs_total_equity = None\n",
    "\n",
    "for i, symbol in enumerate(tickers.keys()):\n",
    "    df = pd.read_csv(os.path.join(out_path, f'{symbol}0.csv'))\n",
    "    df.index = pd.to_datetime(df['timestamp'])\n",
    "    equity = df['balance'] + df['position'] * df['mid_price']\n",
    "\n",
    "    equity_5min = equity.resample('5min').last()\n",
    "\n",
    "    notional_trade_value = df['position'].diff().abs().rolling('1d').sum().resample('1d').last() * df['mid_price'].resample('1d').last()\n",
    "    # order_qty is set to approximately $100.\n",
    "    approx_num_trades = notional_trade_value / 100\n",
    "    avg_approx_num_trades = approx_num_trades.mean()\n",
    "\n",
    "    # Due to size limitations, individual equity curves are cleared in the output.\n",
    "    fig = plt.figure(i, figsize=(12, 6))\n",
    "    ax = fig.add_subplot(111)\n",
    "    ax.set_title(f'{symbol}, approximate number of average daily trades: {avg_approx_num_trades:.0f}')\n",
    "    ax.set_ylabel('Equity $')\n",
    "    ax.plot(equity_5min)\n",
    "    ax.legend(['Equity'])\n",
    "    ax_pos = ax.twinx()\n",
    "    ax_pos.set_ylabel('Position Qty')\n",
    "    ax_pos.plot(df['position'].resample('5min').last(), 'gray', alpha=0.5)\n",
    "    ax_pos.legend(['Position Qty'])\n",
    "\n",
    "    # Selects only the positive ones, we will test this set in different months and the forward month as well.\n",
    "    if equity.iloc[-1] > 0:\n",
    "        sel_pairs.append(symbol)\n",
    "        if sel_pairs_total_equity is None:\n",
    "            sel_pairs_total_equity = equity_5min\n",
    "        else:\n",
    "            sel_pairs_total_equity += equity_5min"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "04bd96b4-40e0-47c0-84d3-55c10b5ef0e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fc40097ed90>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "plt.title(f'{len(sel_pairs)} pairs are selected out of {len(tickers)}')\n",
    "plt.ylabel('Equity $')\n",
    "plt.plot(sel_pairs_total_equity)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a8e9f53b-0bec-4865-90c4-34bb180d1f28",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
